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A ZigBee-based mobile tracking system through wireless sensor networks

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TLDR
This paper proposes a decentralised ZigBee-based tracking system to detect and track the location of mobile nodes indoors based on the received signal strength (RSS), which does not require additional hardware, depends on a new weight function, and can be deployed wherever the node density is low.
Abstract
Wireless sensor networks have been deployed widely. Sensor networks involve sensor nodes which are very small in size, low in cost and have a short battery-life. One of the critical wireless sensor network applications is localisation and tracking mobile sensor nodes. ZigBee is a new emerging technology for low rate, low power and low range communication networks, which aims to provide long battery life for network devices. In this paper, we discuss various localisation and tracking techniques and categorise these techniques based on the communication between nodes in centralised and decentralised localisation systems. We propose a decentralised ZigBee-based tracking system to detect and track the location of mobile nodes indoors based on the received signal strength (RSS). The proposed tracking system is a range-free system, which does not require additional hardware, depends on a new weight function, and can be deployed wherever the node density is low. The tracking system is implemented by ZigBee sensor devices, and experiments are done to evaluate the proposed tracking system based on accuracy and communication cost.

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Posted Content

An Indoor Fingerprinting Localization Approach for ZigBee Wireless Sensor Networks

TL;DR: The proposed fingerprinting localization approach does not require gathering a large number of reference points and offers good localization accuracy indoors, and the implemented approach is based on dividing the tracking area into subareas and assigning a unique feature to each subarea through ranging the RSS values from different reference points.
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Indoor localization using time difference of arrival with UWB signals and unsynchronized devices

TL;DR: An indoor localization system based on TDoA for UWB is proposed that implements an only one way transmission ranging algorithm to measure the time differences of arrival and shows an improvement in terms of localization accuracy that the algorithm allows compared to fingerprinting methods.
References
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Book

Wireless Communications: Principles and Practice

TL;DR: WireWireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design as discussed by the authors, which covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs).
Journal ArticleDOI

GPS-less low-cost outdoor localization for very small devices

TL;DR: This work reviews localization techniques and evaluates the effectiveness of a very simple connectivity metric method for localization in outdoor environments that makes use of the inherent RF communications capabilities of these devices.
Journal ArticleDOI

A Probabilistic Approach to WLAN User Location Estimation

TL;DR: The feasibility of this approach is demonstrated by reporting results of field tests in which a probabilistic location estimation method is validated in a real-world indoor environment.
Journal ArticleDOI

Statistical learning theory for location fingerprinting in wireless LANs

TL;DR: Techniques and algorithms developed in the framework of Statistical Learning Theory are applied to the problem of determining the location of a wireless device by measuring the signal strength values from a set of access points (location fingerprinting), with the advantage of a low algorithmic complexity in the normal operating phase.
Proceedings ArticleDOI

Weighted Centroid Localization in Zigbee-based Sensor Networks

TL;DR: Weighted centroid localization (WCL) provides a fast and easy algorithm to locate devices in wireless sensor networks that is derived from a centroid determination which calculates the position of devices by averaging the coordinates of known reference points.
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